A heterogeneous network (HetNet) has been considered a development of the current radio network coverage technology. In the heterogeneous network, there are arranged, in addition to normal base stations (e.g., macro base stations (macro eNodeB)) used in 2G, 3G, 4G, LTE or LTE-A network, many low-power nodes (e.g., pico base stations (pico eNodeB), femto base stations (femto eNodeB), relay stations, micro base stations (micro eNodeB) etc.). These low-power nodes contribute to improvement in cell's total throughput and cell coverage. Since a normal base station and a low-power node are both transmission points in a heterogeneous network, a user connected to such a low-power node suffers from strong interference from the normal base station which covers the same area as the low-power node. Particularly, once the coverage of the low-power node is extended by applying a fixed offset (bias), a user of the normal base station may access the low-power node to become a low-power node user, who thereby may suffer from stronger interference from the normal base station. Accordingly, in the heterogeneous network, there is a need to use enhanced inter-cell interference coordination (eICIC).
In the current 3GPP standardization, a study about eICIC is mainly focused on reduction in interference of a normal base station which a low-power node user suffers from by switching the normal base station between mute and non-mute per time interval. For example, in 3GPP Rel. 10, semi-static eICIC has been studied intensively. In this technique, the normal base station is controlled as to open and closed (mute/non-mute) states based on a preset transmission pattern. Such a pattern may be called ABS pattern (almost blank subframe pattern) or muting pattern. However, if the transmission pattern is fixed in each transmission time interval (TTI), it is not optimal for cell total throughput. Accordingly, there is proposed a dynamic eICIC technique.
According to the flow of the dynamic eICIC, in order to improve cell total throughputs, the normal base station dynamically determines the mute/non-mute state of data transmission of the own station in each TTI or over a plurality of TTIs. For example, in the dynamic eICIC, in determining the mute/non-mute state of the macro base station, there is a need to compare cell performance between a case of macro base station without transmission (macro mute) and a case of macro base station with transmission (macro non-mute). Here, the mute state of the macro base station corresponds to the case of macro base station without transmission and the non-mute state of the macro base station corresponds to the case of macro base station with transmission. In transmission decision (muting decision), the macro base station compares a sum of capacities of all transmission points for the case of macro base station without transmission with a sum of capacities of all transmission points for the case of macro base station with transmission, and selects the state of higher capacity. As compared with the semi-static eICIC, some improvement of performance is expected in the dynamic eICIC.
FIG. 1a is a view illustrating cover areas of a macro base station and each low-power node in the case of macro base station without transmission (mute state), where the system performance in this case represents a sum of capacities of all users accessing to low-power nodes. FIG. 1b is a view illustrating cover areas of a macro base station and each low-power node in the case of macro base station with transmission (non-mute state), where the system performance in this case represents a sum of capacities of all users accessing to the low-power nodes and all macro users. Here, each macro user is a user accessing the macro base station. Comparing capacities of these two cases, a case of higher capacity is selected to be an actual state of the macro base station. Here, the area enclosed in the solid line represents coverage of the macro base station, the coverage that is not filled (blank) represents the mute state of the macro base station, and the coverage that is filled in a lattice pattern represents the non-mute state of the macro base station. The area enclosed in the dotted line represents coverage of each low-power node.
Specifically, the capacities of the above-mentioned two cases are estimated by the transmission points based on channel quality indicators (CQIs) fed back from users. FIG. 2 is a view illustrating the process of a user feeding back a CQI to a transmission point. The feedback time interval is set by the system, for example, 10 ms. In FIG. 2, the macro user feeds a CQI for the non-mute state of the macro base station and after a 6-ms propagation delay, the macro base station receives the CQI and estimates a capacity that can be obtained when the own station selects the non-mute state in the next transmission time. Specifically, the macro base station determines the mute/non-mute state of the own station at the time 6 ms based on the CQI at the time 0 ms received from a macro user. Likewise, the macro base station determines the mute/non-mute state of the own station at the time 16 ms based on the CQI at the time 10 ms received from the macro user. A low-power node user feeds back two representative CQIs of the respective cases of non-mute and mute states of the macro base station that covers the low-power node. Here, each unfilled column represents a CQI for the mute state and each filled column represents a CQI for the non-mute state. After receiving these two CQIs, the low-power node can estimate a sum of capacities of all users of the own station for each of the non-mute state and the mute state. Then, the macro base station compares the capacities and executes the transmission decision.